Redash
Metabase
Tableau
Microsoft Power BI
Looker
Google Data Studio
Apache Superset
D3.js
iPython
Jupyter
PyCharm
Spyder
IDLE
PyScripter
Pyzo
Ecere SDK
iPythoniPython might be a bit more popular than Redash. We know about 20 links to it since March 2021 and only 19 links to Redash. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I am looking for service or tool similiar to Metabase or Redash that allows me to add data source - for example Postgres connection, and create raw SQL queries that can be shared or exposed through API. So instead of keeping raw SQL code somewhere, my other service would call this tool e.g. http://microservice/query=1?param1=xx&page=2 and get the results from the DB. These calls are internal only and part of ETL... Source: almost 3 years ago
I have tried Metabase, Redash beore (both self hosted open source versions), from my experience I find Metabase a bit easy to work with. Source: about 3 years ago
Regarding visualization tools, sqliteviz has proven to be the best I've found so far. Their web app runs locally but has some trackers, so I run it locally via a simple, static HTTP server. Falcon and Redash seem like overkill for my needs. Source: about 3 years ago
In addition to metabase there are redash[0] and apache superset[1]. They are more or less similar to metabase with some different quirks. You can also visualize quite a bit of data in grafana[2] as well. [0] https://redash.io/ [1] https://superset.apache.org/ [2] https://github.com/grafana/grafana. - Source: Hacker News / over 3 years ago
This is typically called a "dashboard" and there is a whole industry of existing commercial products (for example https://redash.io/) that are built around doing data analysis and visualization. Source: almost 4 years ago
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโฆ. - Source: dev.to / 10 months ago
As alluded to in Poetry2Nix Development Flake with Matplotlib GTK Support, Iโm currently in the process of getting my โnewโ python workflow up to speed. My second problem, after dependency and environment management, was that fancy REPLs like ipython or ptpython donโt jazz well with the standard comint based inferior python repl that comes with python-mode. One can basically only run ipython with the... - Source: dev.to / about 2 years ago
Third, if possible use a command line interpreter to test things out. I recommend ipython for this purpose. You can use your browser's developer console this way if you are learning Javascript. Source: over 3 years ago
IJulia is an interactive notebook environment powered by the Julia programming language. Its backend is integrated with that of the Jupyter environment. The interface is web-based, similar to the iPython notebook. It is open-source and cross-platform. - Source: dev.to / over 3 years ago
Also, take a look at installing iPthon to give you a much richer shell environment. This underpins Jupyter Notebooks, so is well known, proven and trusted. Source: over 3 years ago
Metabase - Metabase is the easy, open source way for everyone in your company to ask questions and learn from...
Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.
Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.
PyCharm - Python & Django IDE with intelligent code completion, on-the-fly error checking, quick-fixes, and much more...
Microsoft Power BI - BI visualization and reporting for desktop, web or mobile
Spyder - The Scientific Python Development Environment